Principal Systems Engineer, Replay Infrastructure - Autonomous Vehicles
NVIDIA has become the platform upon which every new AI-powered application is built. From healthcare research applications to autonomous vehicles, or voice-recognition systems, the need for advanced perception and cognitive capabilities is exploding... and NVIDIA is right in the center of this revolution. As our AV program grows, enabling our internal team to develop AV software is a top priority, as well as enabling our program partners (several major OEMs) to help build our AV code base. At the core of our AV development strategy is the use of on-road logs and sensor data based Replay capability.
In order to deeply analyze and improve our Autonomous Vehicles behavior we need to build a well defined set of sophisticated micro services, tools and infrastructure that works with on-road logs and sensor data captured from vehicles at scale and on a continuous basis. These services and tools will enable AV engineers, algorithm developers, test engineers as well as product teams to measure and understand the comprehensive performance of AV systems built with complex ML models, planning and control systems, and heuristics. Incoming logs would represent immense variation in external conditions and inputs to the AV systems are complex and the outputs are often gradient (non-binary); with monitoring required over time and at various levels. We will rely on these services to be highly effective and user friendly so the users will be effectively focused on building AV that’s superior in the industry.
We are looking for a technical leader to design and build our replay capabilities, including the underlying cloud infrastructure, backends, test execution and debugging frameworks, test tooling, and more.
What you'll be doing:
Architect and build scalable distributed services that will help analyze, evaluate, and understand AV behavior from on-road logs and sensor recordings
Design interfaces, data models, and schemas to support log search and discovery of critical on-road events
Collaborate with multiple AV teams to understand their requirements and use cases to build Replay based Cloud test infrastructure that improves productivity
Define and Deliver rapid iterations of group's technical strategies and roadmaps for effective test management
Define metrics and drive improvements based user feedback and metrics
Partner with our AV and Infrastructure leadership to deliver a cohesive product to customers
What we need to see:
You possess advanced programming skills to build distributed and compute systems, backend services, microservices and cloud technologies
Ability to work optimally with multi-functional teams, principals and architects, across organizational boundaries
Deep technical expertise in GoLang, Python, GraphQL, Temporal, Helm, Prometheus, Kafka, PostgreSQL
Passion for building rich, customer-focused, developer centric applications that involved database, backend, job scheduling and orchestration
Excellent interpersonal skills and the ability to lead multi-functional efforts
BS or MS in Computer Science, Computer Engineering or related field or equivalent experience
15+ years of relevant experience
12+ years of proven experience in performance and/or real-time software technical leadership roles in an agile software development environment
12+ years of demonstrated ability in debugging, performance analysis, and testing system design
Ways to stand out from the crowd:
Highly proficient in simulation, AV/robotics stacks, software testing tools, infrastructure (cloud and on-prem), and user-productivity software
Prior experience in working with large scale log replay of Autonomous vehicles stack in cloud and on target
We are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and talented people in the world working for us. If you're creative and autonomous with a real passion for technology we want to hear from you!The base salary range is 268,000 USD - 414,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.